scholarly journals An in-silico analysis of information sharing systems for adaptable resources management: a case study of oyster farmers

2019 ◽  
Vol 1 ◽  
pp. 16166
Author(s):  
Nicolas Paget ◽  
Bruno Bonté ◽  
Olivier Barreteau ◽  
Gabriella Pigozzi ◽  
Pierre Maurel
Keyword(s):  
Decision Making ◽  
Information Sharing ◽  
In Silico Analysis ◽  
Mortality Rates ◽  
Agent Based ◽  
Resources Management ◽  
Agent Based Modelling ◽  
Share Information ◽  
Silico Analysis

Information sharing systems are often viewed as a potential way of increasing scrutiny by actors of their interactions with natural resources. Scrutiny is then seen as encouraging sustainable and adaptable management of the resource. We tackle this claim by using an agent-based model to focus on the specific issue of oyster farmers dealing with the deadly OsHV-1 virus by sharing information about their own experience (practices and outcomes) via their social network and/or an information sharing system. We followed closely what access to such information sharing means for the environment (production), agents (beliefs) and interactions between the environment and agents (practices). In the model, introducing information sharing leads to a decrease in mortality rates and a convergence in agents’ beliefs. Agents stop changing their practices earlier when they share information, but heterogeneity in agent decision-making models leads to wider exploration of possible strategies and increased production. Agent-based modelling proved a suitable method for studying the impacts of information sharing.

A Comparison between Agent-Based and GIS-Based Tsunami Evacuation Simulations: A Case Study for Tofino, BC

2021 ◽  
Author(s):  
Joseph Kim ◽  
Tomoyuki Takabatake ◽  
Ioan NISTOR ◽  
Tomoya Shibayama
Keyword(s):  
Information Systems ◽  
Geographical Information Systems ◽  
Mortality Rates ◽  
Geographical Information ◽  
Evacuation Planning ◽  
Loss Of Life ◽  
Agent Based ◽  
Agent Based Modelling ◽  
Validation Tool

Soft measures such as evacuation planning are recommended to mitigate the loss of life during tsunamis. Two types of evacuation models are widely used: (1) Agent-based modelling (ABM) defines sets of rules that individual agents in a simulation follow during a simulated evacuation. (2) Geographical information systems (GIS) are more accessible to city planners, but cannot incorporate the dynamic behaviours found in ABMs. The two evacuation modelling methodologies were compared through a case study by assessing the state of evacuation preparedness and investigating potential mitigation options. The two models showed different magnitudes for mortality rates and facility demand but had similar trends. Both models agreed on the best solution to reduce the loss of life for the community. GIS may serve as a useful tool for initial investigation or as a validation tool for ABMs. ABMs are recommended for use when modelling evacuation until GIS methodologies are further developed.

scholarly journals Visualising Ostia’s Processional Landscape Through a Multi-Layered Computational Approach: Case Study of the Cult of the Magna Mater

2019 ◽  
Vol 5 (1) ◽  
pp. 444-467
Author(s):  
Katherine A. Crawford
Keyword(s):  
Network Analysis ◽  
Computational Approach ◽  
Urban Network ◽  
Agent Based ◽  
Agent Based Modelling ◽  
Existing Problems ◽  
Layered Approach ◽  
Religious Landscape ◽  
Insight Into

AbstractOstia, the ancient port of Rome, had a rich religious landscape. How processional rituals further contributed to this landscape, however, has seen little consideration. This is largely due to a lack of evidence that attests to the routes taken by processional rituals. The present study aims to address existing problems in studying processions by questioning what factors motivated processional movement routes. A novel computational approach that integrates GIS, urban network analysis, and agent-based modelling is introduced. This multi-layered approach is used to question how spectators served as attractors in the creation of a processional landscape using Ostia’s Campo della Magna Mater as a case study. The analysis of these results is subsequently used to gain new insight into how a greater processional landscape was created surrounding the sanctuary of the Magna Mater.

scholarly journals Summary of the Available Molecular Methods for Detection of SARS-CoV-2 during the Ongoing Pandemic

2021 ◽  
Vol 22 (3) ◽  
pp. 1298
Author(s):  
Fabio Arena ◽  
Simona Pollini ◽  
Gian Maria Rossolini ◽  
Maurizio Margaglione
Keyword(s):  
Genetic Variability ◽  
Viral Genome ◽  
Molecular Detection ◽  
In Silico Analysis ◽  
Laboratory Diagnosis ◽  
Mortality Rates ◽  
Genomic Evolution ◽  
Review Of The Literature ◽  
The Uk ◽  
Silico Analysis

Since early 2020, the COVID-19 pandemic has caused an excess in morbidity and mortality rates worldwide. Containment strategies rely firstly on rapid and sensitive laboratory diagnosis, with molecular detection of the viral genome in respiratory samples being the gold standard. The reliability of diagnostic protocols could be affected by SARS-CoV-2 genetic variability. In fact, mutations occurring during SARS-CoV-2 genomic evolution can involve the regions targeted by the diagnostic probes. Following a review of the literature and an in silico analysis of the most recently described virus variants (including the UK B 1.1.7 and the South Africa 501Y.V2 variants), we conclude that the described genetic variability should have minimal or no effect on the sensitivity of existing diagnostic protocols for SARS-CoV-2 genome detection. However, given the continuous emergence of new variants, the situation should be monitored in the future, and protocols including multiple targets should be preferred.

Improving the Efficiency of Large-Scale Agent-Based Models Using Compression Techniques

2012 ◽  
pp. 301-326
Author(s):  
Mitchell Welch ◽  
Paul Kwan ◽  
A.S.M. Sajeev ◽  
Graeme Garner
Keyword(s):  
Large Scale ◽  
Agent Based Models ◽  
Agent Based ◽  
Agent Based Modelling ◽  
Livestock Disease ◽  
Interacting Agents ◽  
National Model ◽  
Complex Phenomena ◽  
Modelling System

Agent-based modelling is becoming a widely used approach for simulating complex phenomena. By making use of emergent behaviour, agent based models can simulate systems right down to the most minute interactions that affect a system’s behaviour. In order to capture the level of detail desired by users, many agent based models now contain hundreds of thousands and even millions of interacting agents. The scale of these models makes them computationally expensive to operate in terms of memory and CPU time, limiting their practicality and use. This chapter details the techniques for applying Dynamic Hierarchical Agent Compression to agent based modelling systems, with the aim of reducing the amount of memory and number of CPU cycles required to manage a set of agents within a model. The scheme outlined extracts the state data stored within a model’s agents and takes advantage of redundancy in this data to reduce the memory required to represent this information. The techniques show how a hierarchical data structure can be used to achieve compression of this data and the techniques for implementing this type of structure within an existing modelling system. The chapter includes a case study that outlines the practical considerations related to the application of this scheme to Australia’s National Model for Emerging Livestock Disease Threats that is currently being developed.

Agent-Based Modelling in Multicellular Systems Biology

2020 ◽  
pp. 369-389
Author(s):  
Sara Montagna ◽  
Andrea Omicini
Keyword(s):  
Developmental Biology ◽  
Drosophila Melanogaster ◽  
Systems Biology ◽  
Computational Models ◽  
The Self ◽  
Agent Based Simulation ◽  
Agent Based ◽  
Agent Based Modelling ◽  
Multi Agent

This chapter aims at discussing the content of multi-agent based simulation (MABS) applied to computational biology i.e., to modelling and simulating biological systems by means of computational models, methodologies, and frameworks. In particular, the adoption of agent-based modelling (ABM) in the field of multicellular systems biology is explored, focussing on the challenging scenarios of developmental biology. After motivating why agent-based abstractions are critical in representing multicellular systems behaviour, MABS is discussed as the source of the most natural and appropriate mechanism for analysing the self-organising behaviour of systems of cells. As a case study, an application of MABS to the development of Drosophila Melanogaster is finally presented, which exploits the ALCHEMIST platform for agent-based simulation.

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